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Multi-dimensional Optimization of Groove Parameters in Gas Film Seal

机译:气膜密封槽槽参数的多维优化

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Groove parameters in gas film seal with grooved interface make an obvious impact on the performance of seal system. There are many parameters to describe the geometric features of the groove. In general, a big limitation exists in one-dimensional optimization of groove geometry. Based on particle swarm intelligence algorithm, this article proposed and carried out multi-dimensional optimization of groove geometry in gas film seal, regarded the groove geometry parameters as components of the particle, completed numerical solution of the objective function for the seal performance, and obtained better groove geometry parameters. The example showed that the effect that every geometry dimension plays on the steady-state characteristics of cylindrical gas film seal is not independent, and the multi-dimensional optimization method effectively improves the results of the objective function value. The proposed method can be used for the dimensional optimization design of groove geometry in both cylinder and face gas film seal.
机译:带槽界面的气体膜密封中的沟槽参数对密封系统的性能产生明显影响。有许多参数来描述凹槽的几何特征。通常,凹槽几何形状的一维优化存在大的限制。基于粒子群智能算法,本文提出和进行了气膜密封中的凹槽几何形状的多维优化,将凹槽几何参数作为粒子的组分,完成了密封性能的目标函数的数值溶液,并获得了更好的凹槽几何参数。该示例显示,每个几何维度在圆柱形气体膜密封件的稳态特性上播放的效果不是独立的,并且多维优化方法有效地提高了目标函数值的结果。所提出的方法可用于两个气缸和面部气膜密封中的凹槽几何形状的尺寸优化设计。

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